Monitoring of patient cardio-respiratory events is of vital clinical importance in the early detection of potentially fatal conditions. Current technologies that involve contact sensors require that the individual wears such devices constantly. Such a requirement can lead to discomfort, psychological dependence, loss of dignity, and may even cause additional medical issues such as skin infection when sensors have to be worn for an extended period of time. Elderly patients, infants, and those suffering from chronic medical conditions are more likely to suffer from such negative effects of continuous monitoring. The use of an unobtrusive, non-contact, imaging based monitoring of physiological events can go a long way towards alleviating some of these issues.
Previous methods by the authors hereof and other Xerox researchers, have been directed to systems and methods which employ video image devices for monitoring a patient for a desired physiological function in a non-contact, remote sensing environment. In these methods, videos are captured of a region of interest of the resting patient and processed to estimate cardiac and respiratory functions from physiological signals extracted from time-series signals obtained from those videos. Xerox researchers have determined that movement by the resting patient such as a turning of the head, moving an arm, and the like, may impart or induce motion artifacts into the physiological signals extracted from the video of that patient. This is of particular concern when the subject being monitored by video sensing is an infant in a neonatal intensive care unit. Movement of the patient needs to be accounted for in physiological signals extracted from time-series signals obtained from videos.
Accordingly, what is needed in this art is a system and method for compensating for motion induced artifacts in physiological signals obtained from multiple videos captured by multiple video imaging devices of a subject being monitored for a desired physiological function in a non-contact, remote sensing environment.